Coexistence of Wi Fi and heterogeneous small cell networks sharing unlicensed spectrum

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Zhang, Haijun, Chu, Xiaoli, Guo, Weisi and Wang, Siyi. (2015) Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum. IEEE Communications Magazine, Volume 53 (Number 3). pp. 158-164.

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Coexistence of Wi-Fi and Heterogeneous Small

Cell Networks Sharing Unlicensed Spectrum

Haijun Zhang, Xiaoli Chu, Weisi Guo and Siyi Wang

Abstract

As two major players in terrestrial wireless communications, Wi-Fi systems and cellular networks

have different origins and have largely evolved separately. Motivated by the exponentially increasing

wireless data demand, cellular networks are evolving towards a heterogeneous and small cell network

architecture, wherein small cells are expected to provide very high capacity. However, due to the limited

licensed spectrum for cellular networks, any effort to achieve capacity growth through network

densi-fication will face the challenge of severe inter-cell interference. In view of this, recent standardization

developments have started to consider the opportunities for cellular networks to use the unlicensed

spectrum bands, including the 2.4 GHz and 5 GHz bands that are currently used by Wi-Fi, Zigbee

and some other communication systems. In this article, we look into the coexistence of Wi-Fi and 4G

cellular networks sharing the unlicensed spectrum. We introduce a network architecture where small

cells use the same unlicensed spectrum that Wi-Fi systems operate in without affecting the performance

of Wi-Fi systems. We present an almost blank subframe (ABS) scheme without priority to mitigate

the co-channel interference from small cells to Wi-Fi systems, and propose an interference avoidance

scheme based on small cells estimating the density of nearby Wi-Fi access points to facilitate their

coexistence while sharing the same unlicensed spectrum. Simulation results show that the proposed

network architecture and interference avoidance schemes can significantly increase the capacity of 4G

heterogeneous cellular networks while maintaining the service quality of Wi-Fi systems.

Index Terms

Wi-Fi, heterogeneous network, small cell, LTE/LTE-A, unlicensed spectrum sharing.

I. INTRODUCTION

In recent years, the mobile data usage has grown by 70–200% per annum. More worryingly, the bursty nature of wireless data traffic makes traditional network planning for capacity obsolete. Amongst both operators and vendors alike, small cells (e.g., picocells, femtocells and relay nodes) have been considered as a promising solution to improve local capacity in traffic hotspots, thus relieving the burden on overloaded macrocells. A lot of research and development efforts have been made to efficiently offload excess traffic from macrocells to small cells, especially in indoor environments [1].

Due to the scarcity of licensed spectrum for cellular networks, small cells are expected to share the same spectrum with macrocells even when they are deployed within the coverage area of a macrocell [2]. A frequency reuse factor of 1 in 3G HSPA+ and 4G LTE/LTE-A systems has proven to yield high gains in network capacity. If without notable amounts of extra spectrum made available for mobile communications, future cellular networks will unsurprisingly continue to explore aggressive frequency reuse methods. Accordingly, the envisaged large-scale deployment of small cells is likely to be hampered by the potentially severe co-channel interference between small cells and the umbrella macrocell and between neighboring small cells in dense deployment. In view of this, the wireless industry is examining the efficient utilization of all possible spectrum resources including unlicensed spectrum bands to offer ubiquitous and seamless access to mobile users [3]. The unlicensed 2.4 GHz and 5 GHz bands that Wi-Fi systems operate in have been considered as important candidates to provide extra spectrum resources for cellular networks. The initially targeted 5 GHz unlicensed band has potentially up to 500 MHz of spectrum available. In USA, Korea and China, deploying LTE-A in unlicensed spectrum does not require changes to the existing LTE-A standards (e.g., 3GPP Rel-10). In most other countries, the regulatory requirements of ‘Listen Before Talk’ in unlicensed spectrum mandate standard modifications (e.g., candidates for 3GPP Rel-13).

while the proliferation of Wi-Fi access points continues. The Wi-Fi access point density in developed urban areas has reached over 1000 per square km. Widely deployed Wi-Fi systems are playing an increasingly more important role in offloading data traffic from the heavily loaded cellular network, especially in indoor traffic hot-spots and in poor cellular coverage areas. Very recently, the FCC voted to make 100 MHz of spectrum in the 5 GHz band available for unlicensed Wi-Fi use, giving carriers and operators more opportunities to push data traffic to Wi-Fi. Wi-Fi access points have even been regarded as a distinct tier of small cells in heterogenous cellular networks. However, since Wi-Fi systems are wireless local area networks (WLANs) based on the IEEE 802.11 standards, they have usually been designed and deployed independently from the cellular networks. Now that the wireless industry is seeking to explore the unlicensed spectrum currently used by Wi-Fi systems for LTE/LTE-A and future cellular networks’ usage as well, the coexistence and interworking of Wi-Fi and heterogeneous cellular networks become an area requiring extensive research and investments. The joint deployment of Wi-Fi and cellular networks in the unlicensed spectrum can increase the overall capacity of a heterogeneous network, provided that the mutual interference between Wi-Fi and cellular systems is properly managed so that both can harmoniously coexist.

MHz band in USA, with the primary cell always operating in the licensed band. Verizon and Ericsson are also exploring similar ideas. Huawei and CMCC have investigated the availability, commonality and feasibility of integrating the unlicensed spectrum to International Mobile Telecommunications-Advanced (IMT-A) cellular networks [3]. LTE-Unlicensed (LTE-U) was first proposed by Qualcomm and Ericsson as a technology to run LTE in unlicensed spectrum in congested areas. Since February 2014, NTT DoCoMo and Huawei have been researching LTE-U, which they refer to as Licensed-Assisted Access using LTE (LAA-LTE). They have demonstrated on pre-commercial multi-cell networks that LAA-LTE achieves better coverage and capacity in the 5 GHz unlicensed spectrum than Wi-Fi alone. However, there are still concerns that LTE-U may completely take over the Wi-Fi bands in dense deployments.

It is worth noting that technical issues related to the coexistence of Wi-Fi and heterogeneous cellular networks in unlicensed spectrum, such as efficient spectrum sharing and interference mitigation, have not been sufficiently addressed. In [10], the authors proposed an integrated architecture exploiting the opportunistic networking paradigm to migrate data traffic from cellular networks to metropolitan Wi-Fi access points. In [11], Benniset al.introduced the basic building blocks of cross-system learning and provided preliminary performance evaluation in an LTE simulator overlaid with Fi hotspots. For the unlicensed spectrum sharing deployment of Wi-Fi and LTE-A systems, the co-channel interference between Wi-Wi-Fi tier and LTE-A tier can be mitigated by using ABSs, in which the interfering tier is not allowed to transmit data, and the victim tier can thus get a chance to schedule transmissions in the ABSs with reduced cross-tier interference [12]. Moreover, it has been shown that by estimating the number of co-channel transmitters and knowing the deployment density of network nodes in a region, the average channel quality at any point in a coverage area can be inferred [13].

spectrum sharing between small cells and Wi-Fi access points. Simulation results are provided to evaluate the performance of the proposed network architecture and interference avoidance scheme in facilitating coexistence of Wi-Fi and 4G heterogeneous cellular networks in unlicensed spectrum.

Macro BS

MUE MUE

UE UE

D2D

Small Cell BS/Wi-Fi

Small Cell BS UE

mmWave backhual link

U-plane (RRC)

C-plane

Split

Primary Carrier Licensed Spectrum

Secondary Carrier Unlicensed Spectrum

Unlicensed Spectrum

Wi-Fi

unlicensed spectrum link CN

CN GW

Fig. 1. Network Architecture of LTE-A and Wi-Fi Coexistence.

II. NETWORKARCHITECTURE FOR WI-FI ANDCELLULARCOEXISTENCE A. Heterogeneous Network Architecture

band, while the U-plane of UEs associated with a small cell is provided by their serving small cell in a high frequency band. For UEs associated with the macrocell, both the C-plane and U-plane of their radio links are provided by the serving macrocell. Since the C-plane of small-cell UEs is managed by the macrocell, the radio resource control (RRC) signallings of small-cell UEs are transmitted from the macrocell, and the handover signalling overhead between small cells and the macrocell can be much reduced [6]. Regarding Wi-Fi access points as a type of small cells, the C-plane and U-plane split can be applied in a Wi-Fi/Macrocell scenario, where the C-plane of UEs associated with a Wi-Fi access point is provided by the macro eNB in a low licensed frequency band, while the U-plane of UEs associated with a Wi-Fi access point is provided by their serving Wi-Fi access point in a high unlicensed frequency band. The interworking of Wi-Fi and cellular networks benefits from the split of C-plane and U-plane in terms of mobility robustness, service continuity, reduction in cell-planning efforts, energy efficiency, etc.

When considering the backhaul issues of small cells, expensive wired backhaul links may not always be feasible, especially for the dense deployment of small cells. In the meanwhile, in-band wireless backhaul solutions using the licensed spectrum may not be feasible either, because of the scarcity of the licensed spectrum [7]. Recently, the millimeter-wave bands, such as the unlicensed 60 GHz band and the low interference licensed 70 GHz and 80 GHz bands, have been considered as promising candidates for the small cell backhaul solution. This is motivated by the huge frequency bandwidth (globally harmonised over more than 6 GHz millimeter-wave spectrum) that can be exploited, and the spatial isolation supported by highly directional beams. At the same time, the new IEEE 802.11ad standard, a.k.a. WiGig, uses the unlicensed 60 GHz millimeter-wave band to deliver data rates of up to 7 Gbps. This adds a large amount of new frequency bandwidth to existing Wi-Fi products, such as 802.11n operating in the 2.4 GHz and 5 GHz bands, and 802.11ac operating in the 5 GHz band.

cost taken into account. As can be seen from Fig. 1, the primary carrier always uses licensed spectrum to transmit control signaling, user data and mobility signalling, while the secondary carrier(s) use unlicensed spectrum to transmit best-effort user data in the downlink and potentially the uplink.

B. Handover Procedure between Wi-Fi and LTE/LTE-A

Source Wi-Fi

(MBS) CN GW

Target MBS (Wi-Fi)

Path Switch Request Ack

UE

RRC Conn. Reconf.

RRC Conn. Reconf. Complete

Path Switch Request

UE Context Release Handover Request Ack

Handover Request

Handover Request Ack Handover

decision

Security Context Handover Request

Release Resources

Fig. 2. Handover Procedure between Wi-Fi and LTE/LTE-A.

LTE/LTE-A systems is not supported, although it is badly needed due to users’ frequent mobility between the coverage areas of Wi-Fi access points and cellular networks. In 3GPP Rel-11, trusted WLAN access to the Enhanced Packet Core (EPC) is based on S2a-based Mobility over GPRS Tunnelling Protocol (SaMOG), which is enhanced in 3GPP Rel-12 to provide traffic steering and mobility between LTE-A and Wi-Fi networks and to optimize the use of network resources. The 3GPP standard TS 23.401 describes seamless and non-seamless handover solutions between 3GPP and non-3GPP access networks. These standards enable users to continue using data services when they pass across macrocells, small cells and Wi-Fi hotspots. In the network architecture shown in Fig. 1, a UE can handover between Wi-Fi and cellular networks through the core network (CN) gateway (GW). In Fig. 2, the CN GW based handover procedure between a source Fi (macrocell) and a target macrocell (Fi) is given. Since the C-plane of Wi-Fi UEs is managed by the macrocell, the RRC signallings of Wi-Wi-Fi UEs are transmitted from the macrocell, and the handover signalling overhead between the Wi-Fi access point and the macrocell can be much reduced.

III. ALMOSTBLANK SUBFRAMESALLOCATION A. Co-existence without Priority

In recent years, regulatory bodies are considering the possible co-existence of multiple dis-parate radio access technologies (RATs) on the same frequency band. This includes both the licensed bands (e.g., TV spectrum) and unlicensed bands (e.g., amateur spectrum). In countries such as the USA, Canada, and the UK, regulatory efforts are being made to permit the operation of white space devices (WSDs). For example, the IEEE 802.22 fixed point-to-point cognitive radio transmissions in TV white space, and more recently the IEEE 802.16h wireless broadband protocols.

to each other. In the unlicensed bands without the concepts of primary and secondary users, a similar challenge exists between different RATs sharing the same spectrum.

In this article, we refer to the co-existence of two RATs without priority ranking as co-existence without priority. More specifically, we focus on allowing cellular communications to co-exist with Wi-Fi communications on an equal basis, i.e., no discrimination between primary and secondary users. What is new here is the coexistence of two disparate RATs that were not designed to be in coexistence, together with the impact of this on the interference map. Whilst the co-existence of contention based systems have been explored (e.g., 802.11 and 802.15 systems) [8], the co-existence of a non-contention system (LTE) with a contention system (Wi-Fi) is not well explored, especially when no priority ranking between them is given. In fact, a reasonable suspicion is that the allocation based transmission protocols of LTE may completely block the collision based protocols of Wi-Fi. Coupled with the growing density of small cells, this lack of interpretability on the same spectrum band can cause severe capacity issues.

In multiple RAT coexistence, communication protocols can operate in either their default normal mode or a coexistence mode. The latter is triggered when another RAT is sensed nearby and action is needed. Coexistence mechanisms can be divided into two groups: i) those that require message exchange between nodes or RATs, and ii) those that do not. In general, cross-RAT coordination is difficult due to the disparate protocol development processes and vendor differences. Therefore, in the following sub-section we will review a non-collaborative coexistence mechanism that allows LTE to co-exist with Wi-Fi in the unlicensed spectrum.

B. Random Almost Blank Subframe Allocation

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 10

20 30 40 50 60 70 80 90

LTE Traffic Load

Maximum Achievable Throughput per Cell

LTE − Original Mode WiFi without ABS LTE − 30% ABS WiFi with ABS

Improvement with ABS

Degradation with ABS

Fig. 3. Maximum achievable throughput (Mbits/s per cell) for an LTE or Wi-Fi cell under different normalized traffic loads (normalized to cell capacity), with LTE operating with: a) original mode, and b) ABS.

of different RATs, coordination messaging between cells of different RATs is challenging for the previously mentioned reasons. Therefore, ABSs are transmitted randomly at some rate without coordination and without the need for backwards compatibility with previous releases on the unlicensed bands [9]. The central conceit to this idea is that during the random ABSs, the Wi-Fi access points can detect the channel vacancy and transmit following its contention based protocol. Accordingly, the allocation nature of LTE transmissions can be suppressed in a way that avoids coordination or spectrum sensing, but at the cost of decreased LTE spectral efficiency and network capacity.

TABLE I

SIMULATIONPARAMETERS.

Parameter Value

LTE Carrier Frequency 2100 MHz Wi-Fi Carrier Frequency 2400 MHz LTE Cell Density 3 per km2 Wi-Fi Density 300 per km2 LTE Cell Transmit Power 40 W

Wi-Fi Transmit Power 1 W

Pathloss 3GPP Urban Micro

Peak LTE Throughput 84 Mbits/s (64 QAM SISO) Peak 802.11n Throughput 65 Mbits/s (64 QAM SISO)

increased interference. LTE cell capacity decays slower than Wi-Fi capacity. The super-linear

degradation of Wi-Fi capacity may finally lead to 0 Mbps. By employing 30% ABSs in LTE, the Wi-Fi capacity is improved significantly at high LTE traffic loads, while the LTE cell capacity falls by 10–24 Mbps. Note that the capacity degradation rates for both LTE and Wi-Fi become slower with LTE ABS transmissions, because random ABSs mitigate both cross-tier and co-tier inter-cell interference. It is worth noting that the overall aggregate capacity of LTE and Wi-Fi is actually reduced with ABS, indicating that the random ABS mechanism benefits fairness instead of overall capacity.

In summary, ABSs can be transmitted randomly by LTE transmitters to allow the spectrum-sharing coexistence of allocation-based LTE transmissions and contention-based Wi-Fi transmis-sions with an improved fairness between them, but at the cost of decreased overall aggregate capacity of LTE and Wi-Fi networks.

IV. INTERFERENCE AVOIDANCE WITH NEIGHBORHOODWI-FI DENSITY ESTIMATION A. Inference Framework

Specifically, each BS in an OFDMA system needs to know whether its neighboring BSs are transmitting on each available radio resource block. This level of coordination taxes the back-haul capacity, while any delay in information sharing may cause the interference avoidance performance to falter.

In [13], an interference estimation technique that does not require information sharing between BSs or UEs was devised based on each BS sensing the spectrum and estimating the number of channel transmissions in a defined observation zone. By estimating the number of co-channel transmitters and knowing the cell density in the region, the average co-channel quality at any random point in a coverage area can be inferred. As the expressions are tractable, the computational complexity is extremely low. The methodology can be applied to a K-tier heterogeneous network by leveraging a stochastic geometry framework and an opportunistic interference reduction scheme, which was shown to approach the interference estimation accuracy achievable by information exchange on the X2 interface [13].

The inference framework assumes that each cell is equipped with a spectrum sensing device

1_{. On each frequency band f, the sensor at each cell (located at distance h from the BS) is}

able to detect the power density Pf from all co-channel transmitters in an unbounded region.

Given knowledge of the spatial distribution of co-channel cell deployments [15], the density of co-channel transmissions λf can be inferred from the Pf measurements [13]:

λf ∝ p

Pf/P

Q(h, α) (1)

where α is the pathloss distance exponent, P is the average transmit power of the BSs, and the function Q(h, α) is given in [13]. Without loss of generality, this inference framework can be applied to aK-tier heterogeneous network comprised of macrocells, femtocells and Wi-Fi access points. Fig. 4 illustrates how a femtocell infers the number of co-channel transmitters in a 3-tier heterogeneous network by sensing the received power spectrum. In this illustrative example, the estimated transmitter activities on the considered frequency band are: 50% of LTE macrocells, 100% of LTE femtocells, and 25% of Wi-Fi access points. This spectrum sensing mechanism

1

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!"#$%&'()%**#

!"#$%&'()%**# +,%-./-01# !"#23)4(#5,#

!"#23)4(#5,#

,6%)'47&#,%-./-08#9(:%4#;%-./'<#3'#;/==%4%-'#$4%>7%-)<#53-?.# @ABCDD##

E/F$/#

@ABCDD## E/F$/# @ABCDD##

E/F$/# @ABCDD##

E/F$/#

Fig. 4. Illustration of a femtocell inferring the number of co-channel transmitters from a 3-tier cellular and Wi-Fi heterogeneous network by sensing the received power spectrum [13].

is not able to know which cells are transmitting, but it provides a statistical notion for a BS to infer the channel quality of a served user.

Based on the inferred density of co-channel transmissions λf in the vicinity, the

58

43 _{41 40}

43

35 _{33 33}

58

48 _{45 44}

82

57 59

22 77

57 ₅₃

51

Low Traffic (0.1) Medium Traffic (0.3) High Traffic (0.7) Peak Traffic (1.0)

Peak Cell Capacity (Mbps/Cell)

HFR1 HFR3 SFR P0.5 Coordinated SGC Uncoordinated Avoidance

Fig. 5. Plot of peak cell capacity versus different normalized cell traffic loads for a variety of static and dynamic interference mitigation schemes [13], [14].

as:

SIRf,d ∝Pf−1

Q(h, α)

Q(d, α)

2

, (2)

where the constant of proportionality is the received signal strength.

B. Simulation Results

C. Discussion and Challenges

The disadvantage with a TDD-based coordinated interference avoidance scheme is the need for two prerequisites [14]: (1) cell pairing or clustering; (2) static or dynamic assignment of cell priority. Effective cell pairing often involves the association of cells that are dominant interferers to each other. However, this may not always be the case. For example, the antenna bore-sight of BS A is pointing at BS B, but the antenna bore-sight of BS B is pointing at a direction away from BS A. Alternatively, two cells that are closest to each other will be paired together. Cell priority assignment refers to the process of assigning different transmission priorities to cells. Random access, traffic weighted, and QoS weighted cell priority assignments have been considered in the literature.

V. CONCLUSION

In this article, we have looked into the potentials and challenges associated with coexisting Wi-Fi systems and heterogeneous cellular networks sharing the unlicensed spectrum. We have introduced the network architecture for LTE/LTE-A small cells to exploit the unlicensed spectrum already used by Wi-Fi systems. The ABS mechanism and an interference avoidance scheme have been presented to mitigate the interference between Wi-Fi and LTE/LTE-A systems when both transmitting in the same unlicensed spectrum. Simulation results have shown that with the proper use of ABS mechanism and interference avoidance schemes, heterogeneous and small cell networks can improve their capacity by using the unlicensed spectrum used by Wi-Fi systems without affecting the performance of Wi-Fi.

ACKNOWLEDGMENT

This work was supported by the National Natural Science Foundation of China (61471025), the Fundamental Research Funds for the Central Universities (Grant No. ZY1426), and the Interdisciplinary Research Project in BUCT.

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